Beyond Benford's Law: Distinguishing Noise from Chaos.

Beyond Benford's Law: Distinguishing Noise from Chaos.

Determinism and randomness are two inherent aspects of all physical processes. Time series from chaotic systems share several features identical with those generated from stochastic processes, which makes them almost undistinguishable. In this paper, a new method based on Benford's law is desig...

Full description

Bibliographic Details
Main Authors: Qinglei Li, Zuntao Fu, Naiming Yuan
Format: Article
Language:English
Published: Public Library of Science (PLoS) 2015-01-01
Series:PLoS ONE
Online Access:https://doi.org/10.1371/journal.pone.0129161
id doaj-68b3dd3450dd4380ac5f98d30901453e
record_format Article
spelling doaj-68b3dd3450dd4380ac5f98d30901453e2021-03-03T20:03:21ZengPublic Library of Science (PLoS)PLoS ONE1932-62032015-01-01106e012916110.1371/journal.pone.0129161Beyond Benford's Law: Distinguishing Noise from Chaos.Qinglei LiZuntao FuNaiming YuanDeterminism and randomness are two inherent aspects of all physical processes. Time series from chaotic systems share several features identical with those generated from stochastic processes, which makes them almost undistinguishable. In this paper, a new method based on Benford's law is designed in order to distinguish noise from chaos by only information from the first digit of considered series. By applying this method to discrete data, we confirm that chaotic data indeed can be distinguished from noise data, quantitatively and clearly.https://doi.org/10.1371/journal.pone.0129161
collection DOAJ
language English
format Article
sources DOAJ
author Qinglei Li
Zuntao Fu
Naiming Yuan
spellingShingle Qinglei Li
Zuntao Fu
Naiming Yuan
Beyond Benford's Law: Distinguishing Noise from Chaos.
PLoS ONE
author_facet Qinglei Li
Zuntao Fu
Naiming Yuan
author_sort Qinglei Li
title Beyond Benford's Law: Distinguishing Noise from Chaos.
title_short Beyond Benford's Law: Distinguishing Noise from Chaos.
title_full Beyond Benford's Law: Distinguishing Noise from Chaos.
title_fullStr Beyond Benford's Law: Distinguishing Noise from Chaos.
title_full_unstemmed Beyond Benford's Law: Distinguishing Noise from Chaos.
title_sort beyond benford's law: distinguishing noise from chaos.
publisher Public Library of Science (PLoS)
series PLoS ONE
issn 1932-6203
publishDate 2015-01-01
description Determinism and randomness are two inherent aspects of all physical processes. Time series from chaotic systems share several features identical with those generated from stochastic processes, which makes them almost undistinguishable. In this paper, a new method based on Benford's law is designed in order to distinguish noise from chaos by only information from the first digit of considered series. By applying this method to discrete data, we confirm that chaotic data indeed can be distinguished from noise data, quantitatively and clearly.
url https://doi.org/10.1371/journal.pone.0129161
work_keys_str_mv AT qingleili beyondbenfordslawdistinguishingnoisefromchaos
AT zuntaofu beyondbenfordslawdistinguishingnoisefromchaos
AT naimingyuan beyondbenfordslawdistinguishingnoisefromchaos
_version_ 1714824323397582848

Similar Items